Method for configuring a hearing-assistance device with a hearing profile

ABSTRACT

A method includes: generating a hearing profile for a user; accessing a set of hearing-assistance device options, each hearing-assistance device option defining a form factor of a hearing-assistance device, in a set of hearing-assistance devices; accessing an image of an ear of the user; detecting a set of constraining dimensions in the image of the ear of the user; identifying a subset of hearing-assistance device options, in the set of hearing-assistance device options, defining form factors conforming to the set of constraining dimensions; accessing a set of preferences of the user; ranking the subset of hearing-assistance device options based on the set of preferences; selecting a first hearing-assistance device option, from the subset of hearing-assistance device options, corresponding to a highest rank in the subset of hearing-assistance device options; and configuring a first hearing-assistance device represented by the first hearing-assistance device option with the hearing profile.

CROSS-REFERENCE TO RELATED APPLICATIONS

This Application is a continuation of U.S. patent application Ser. No.16/893,297, filed on 4 Jun. 2020, which claims the benefit of U.S.Provisional Application No. 62/857,214, filed on 4 Jun. 2019, both ofwhich are incorporated in their entireties by this reference.

This Application is related to U.S. Pat. No. 10,595,135, filed on 15Apr. 2019, which is incorporated in its entirety by this reference.

TECHNICAL FIELD

This invention relates generally to the field of sound augmentationdevices and specifically to a new and useful method for configuring ahearing-assistance device in the field of sound augmentation devices.

BRIEF DESCRIPTION OF THE FIGURES

FIG. 1 is a flowchart representation of a method;

FIG. 2 is a flowchart representation of one variation of the method; and

FIG. 3 is a flowchart representation of one variation of the method.

DESCRIPTION OF THE EMBODIMENTS

The following description of embodiments of the invention is notintended to limit the invention to these embodiments but rather toenable a person skilled in the art to make and use this invention.Variations, configurations, implementations, example implementations,and examples described herein are optional and are not exclusive to thevariations, configurations, implementations, example implementations,and examples they describe. The invention described herein can includeany and all permutations of these variations, configurations,implementations, example implementations, and examples.

1. METHOD

As shown in FIG. 1, a method S100 for configuring hearing-assistancedevices includes: generating a hearing profile for the user based on ahearing assessment of the user in Block S110; accessing a set ofhearing-assistance device options, each hearing-assistance device optiondefining a form factor of a hearing-assistance device, in a set ofhearing-assistance devices in Block S120; accessing an image of an earof the user in Block S130; detecting a set of constraining dimensions inthe image of the ear of the user in Block S132; identifying a subset ofhearing-assistance device options, in the set of hearing-assistancedevice options, defining form factors conforming to the set ofconstraining dimensions in Block S140; accessing a set of preferences ofthe user in Block S150; ranking the subset of hearing-assistance deviceoptions based on the set of preferences of the user in Block S152;selecting a first hearing-assistance device option, from the subset ofhearing-assistance device options, corresponding to a highest rank inthe subset of hearing-assistance device options in Block S160; andconfiguring a first hearing-assistance device represented by the firsthearing-assistance device option with the hearing profile for the userin Block S170.

One variation of the method S100 includes: generating a hearing profilefor the user based on a hearing assessment in Blocks S110; accessing aset of hearing-assistance device options, each hearing-assistance deviceoption defining a form factor of the hearing-assistance device in BlockS120; detecting a constraining dimension based on an image of the ear ofthe user in Block S132; identifying a first subset of hearing-assistancedevice options in the set of hearing-assistance device options definingform factors conforming to the constraining dimension in Block S140;accessing a set of preferences of the user in Block S150; identifying asecond subset of hearing-assistance device options in the first subsetof hearing-assistance device options most likely to be selected by theuser based on the set of preferences of the user in Block S160;configuring a selected set of hearing-assistance devices represented inthe second subset of hearing-assistance devices with the hearing profilefor the user in Block S170; and dispatching the selected set ofhearing-assistance devices to the user in Block S180.

Another variation of the method S100 includes: generating a hearingprofile of a user based on a hearing assessment in Block S110; accessinga set of hearing-assistance device options, each hearing-assistancedevice option defining a full-on gain of the hearing-assistance device,defining a number of frequency bands of the hearing-assistance device,and defining a form factor of the hearing-assistance device in BlockS120; accessing a set of constraining dimensions representing an ear ofthe user in Block S132; identifying the subset of hearing-assistancedevice options, in the set of hearing-assistance device options definingform factors conforming to the set of constraining dimension, definingfull-on gains greater than the minimum full-on gain, and definingnumbers of frequency channels greater than the minimum number offrequency channels in Block S140; accessing a set of preferences of theuser in Block S150; ranking the subset of hearing-assistance deviceoptions based on the set of preferences of the user in Block S152;selecting a set of highest-ranked hearing-assistance device options fromthe subset of hearing-assistance device options, the set ofhighest-ranked hearing-assistance device options representing a set ofhighest-ranked hearing-assistance devices in Block S160; and configuringeach hearing-assistance device in the set of highest-rankedhearing-assistance devices with the hearing profile of the user in BlockS170.

2. APPLICATIONS

Generally, the method S100 is executed by a system (e.g., a mobilecomputing device executing an application, a computer system, and/or adistributed computer network): to generate a hearing profile of a userrepresenting the hearing deficiency of the user (i.e. an inability tohear soft sounds, a sensitivity to loud sounds, or any other hearingchallenge); to extract ear anatomy information from an image of theuser's ear; to retrieve user preferences for hearing-assistance devices;and to select—from a catalogue of hearing-assistance device options—aset of hearing-assistance devices that satisfy the user's hearing needs,anatomical features, and preferences. The system can, therefore, isolatea subset of distinct hearing-assistance devices that span potentialcombinations of user priorities for hearing-assistance, comfort,aesthetics, battery life, full-on gain (hereinafter “FOG”), etc. Asupplier packager or other entity affiliated with the system may thendeliver (e.g., mail) the subset of devices to the user, and the user mayselect a device from the subset of devices that best aligns with herpriorities—without input from an audiologist or an extensive fittingsession for the hearing-assistance device.

Before selecting a set of hearing-assistance devices for the user, thesystem generates a hearing profile for the user by executing a hearingassessment, wherein the user expresses a preference (e.g., via an A/Btesting protocol) for a particular gain within each frequency band (i.e.channels) of the human-audible sound range (e.g., 20 to 20,000 Hz).Thus, upon executing the hearing assessment, the system can representthe hearing profile of the user as an array, matrix, or discretefunction that relates a specific gain (i.e. relative volumeamplification) to each frequency band. The system can then evaluate eachhearing-assistance device option in a catalogue of hearing-assistancedevice options to determine whether the hearing-assistance device caneffectively differentially amplify and/or attenuate various frequencybands according to the hearing profile of the user. For example, if theFOG of a hearing-assistance device in a particular frequency band isless than a gain specified by the hearing profile of the user or if thehearing-assistance device does not offer a number of channels greaterthan that which is specified by the hearing profile of the user, thenthe hearing-assistance device cannot execute the hearing profile of theuser and can be excluded as an option in the hearing-assistance deviceselection process.

The system can also obtain fitting information in order to select ahearing-assistance device that physically fits a user by prompting (viaa mobile or browser application) the user to record an image of her ear.The system can then process the image of the user's ear (e.g., via. acomputer vision pipeline) in order to obtain a set of constrainingdimensions that correlate with form factors and/or specific sizes ofhearing-assistance devices. For example, the system can detect ormeasure the distance between an end of the user's forward helix (e.g.,where the forward helix intersects the side of the user's head) to thetop of the user's ear canal as a constraining dimension forreceiver-in-canal hearing aids (hereinafter “RIC hearing aids”).Additionally or alternatively, the system can detect the shape and orsize of a user's concha cavum as a constraining dimension for in-the-earhearing aids (hereinafter “ITE hearing aids”). Upon detecting variousconstraining dimensions for each form factor of the hearing-assistancedevices represented in the set of hearing-assistance device options, thesystem can then filter the catalogue of hearing-assistance devices toremove hearing-assistance devices that are not likely to fit the usersuch as hearing-assistance devices of a particular form factor orcharacterized by a particular size.

Furthermore, the system can rank or score a filtered subset of thecatalogue of hearing-assistance devices (i.e. filtered according tosize/shape and sound processing capabilities) according to preferencesexpressed by the user. The system can prompt the user to complete asurvey to provide user preferences such as a preferred form factor,color, price, weight, battery life or any other specification of ahearing-assistance device. The system can then rank (e.g., via a machinelearning model) the hearing-assistance devices according to how likelythey are to be selected by the user (and therefore satisfy theirpreferences at least when compared to other hearing-assistance devicesoffered to the user). The system can also incorporate user preferencesexpressed in return surveys or post engagement surveys to obtainadditional details regarding a user's preference for hearing-assistancedevices.

The system can also select a number of hearing-assistance device optionsbased on the ranked subset of hearing-assistance device options and aset of selection criteria. The system can determine the set of selectioncriteria based on user preferences expressed via a survey. For example,if the user expresses that she would prefer hearing aids of only twoform factors, the system can set selection criteria that exclude allhearing aids that are not characterized by the user's preferred formfactors. Alternatively, the system can utilize selection criteria thatare set by an administrator of the system in order to provide variety inhearing-assistance devices to improve the likelihood of usersatisfaction. For example, the system can set selection criteriaspecifying a selection of the highest-ranked RIC and ITE hearing aids bythe system.

Upon selecting a subset of hearing-assistance devices that satisfy theselection criteria and are likely to result in improvedhearing-assistance, comfort, and general satisfaction of the user basedon a ranking of hearing-assistance device options, the system can promptan administrator or delivery service to deliver the selected subset ofhearing-assistance devices to the user. When the user receives theselected hearing-assistance devices, the user can interface with thesystem via a mobile application in order to configure thehearing-assistance device with the user's hearing profile, therebyproviding a well-fitting and user-preferable hearing-assistance devicewith a hearing profile calculated specifically for the user.

Additionally, the system can further refine the hearing profile of theuser by performing an on-device hearing assessment with each of thehearing-assistance devices that are delivered to the user. Thus, thesystem can fine tune the hearing profile to account for the specificfrequency response of each hearing-assistance device. The system cantrack revisions made to the user's hearing profile during each on-devicehearing assessment to characterize and preemptively adjust a hearingprofile for a particular device.

The system executes blocks of the method to select a set of“hearing-assistance devices” for a user, such as: hearing aids, wearablehearing-related devices (“hearable” devices), earphones/headphones incoordination with microphones, or any other devices capable ofaugmenting incoming sound.

3. EXAMPLES

In one example, a user can interface with the system to obtain a hearingassessment. The system can then generate a hearing profile for the userand prompt the user to order a hearing-assistance device based on thehearing assessment. The system can further prompt the user to record animage of the user's ear. Subsequently, the system can extractconstraining dimensions of the user's ear from the image in order tosize a hearing-assistance device for the user. Furthermore, the systemcan prompt the user to provide specific preferences pertaining to thehearing-assistance device, such as a preferred color or preferred formfactor. Upon receiving the above information, the system can select aset of three hearing-assistance device options for delivery to the userthat best fits the user's hearing needs, the user's ear size, and theuser's expressed preferences, while also offering the user variety inthe space of available hearing-assistance devices.

In one example, the system can select the highest-ranked RIC hearingaid, completely-in-canal hearing aid (hereinafter “CIC hearing aid”),and ITE hearing aid for the user. In another example, the system canselect an RIC hearing aid with the best match for the user's hearingprofile, an RIC hearing aid that best fits the user's ear, and an RIChearing aid that matches the user's color preferences.

In each case, the system can then trigger a delivery of each of theselected hearing aids to the user and can configure each of thehearing-assistance devices with the hearing profile of the user.

4. HEARING ASSESSMENT

Generally, as described in U.S. Pat. No. 10,595,135, which isincorporated by reference in its entirety, the system can generate ahearing profile compensating for hearing deficiency of the user based ona hearing assessment in Block S110. More specifically, the system cangenerate a hearing profile that can be represented as a set (e.g.,represented as an array) of gain values, wherein each gain valuecorresponds to a frequency band in a human-audible frequency range. Inparticular, the system can generate a baseline hearing profileapproximately compensating for hearing deficiency of the user based onthe user's demographic data and an initial hearing test; collectinghearing preferences from the user (e.g., in the form of volumeadjustments) while playing a series of soundbites including spoken(e.g., vocal) phrases, each soundbite characterized by spectral peakswithin particular frequency bands; and refining the baseline hearingprofile to better reflect the user's hearing ability across the audiblespectrum based on these hearing preferences. The system, in Block Silo,utilizes a combination of a microphone, a digital signal processor(e.g., within a personal, computer, laptop, smartphone), and a speaker(e.g., headphones, internal speakers of the signal processing device) toexecute the hearing assessment.

The system can generate a baseline hearing profile that roughly(approximately) compensates for the hearing deficiency of the useraccording to an initial hearing assessment (e.g., a simplifiedaudiogram) of the user and demographic data input by the user (e.g.,age, sex, and/or occupation). For example, the system can render a setof data input fields within a user portal (e.g., a graphic userinterface) in order to record demographic data associated with the user.Additionally, the system can render one or more slider bars (or anyother adjustable user-interface element) with which the user mayindicate the lowest audible volume of a testing tone (e.g., a 5 kHztone) or the lowest volume at which the user can understand speechconcentrated within a particular frequency band. The system can thenestimate (e.g., via machine learning or other statistical techniques) abaseline hearing profile for the user.

After generating the baseline hearing profile for the user, the systemcan further refine the baseline hearing profile to generate a refinedhearing profile for the user and to fully characterize the hearingdeficiency of the user (e.g., in order to recommend particularhearing-assistance device). Thus, the hearing assessment can includeplaying a series of soundbites (e.g., sentences including phonemeshaving specific frequency characteristics) that are selectively outputby the computing device, such as through headphones connected to orpaired with the computing device. During this hearing assessment, thesystem can select a soundbite (i.e. a reproduceable audio signal) with afrequency spectrum predominantly within a particular frequency band. Thesystem can then apply the baseline hearing profile to the soundbite andplay the soundbite for the user. Subsequently, the system can play thesoundbite a second time with altered gain within the particularfrequency band (e.g., by altering the baseline hearing profile withinthe particular frequency band such as in an A/B testing procedure).After listening to the soundbite repeated according to the alteredhearing profile within the frequency band, the user can then form apreference as to which of the soundbites was clearer or more easilyperceived by the user.

The system can then request qualitative feedback from the user regardinghow well the user has comprehended each version of the soundbite. If thesystem detects that the user has expressed a preference for the modifiedhearing profile, then the system can modify the hearing profile of theuser accordingly, thereby providing an improved characterization of theuser's hearing deficiency (e.g., as expressed by the hearing profile ofthe user).

The system can perform the above hearing assessment multiple times forthe same frequency band (e.g., by playing a pair of soundbites withvarious gain values applied within the frequency band) in order torefine the user's hearing deficiency and preferred gain within thatfrequency band. Furthermore, the system can perform the hearingassessment across multiple frequency bands included in the hearingprofile in order to precisely determine the user's hearing preferences.

The system can compile the user's feedback from the hearing assessmenttests into a refined hearing profile that, when applied to an inputaudio signal, enhances (amplifies and/or reduces) select frequencies (atdifferent input volumes) within the audible or vocal spectrum tocompensate for the user's hearing deficiency, thereby enabling the userto better hear sound generally and to comprehend human speech morespecifically. In particular, the system can generate and store therefined hearing profile executable by an audio device to amplify selectfrequencies and thus enable the user to better comprehend human speechgiven feedback collected from the user during a brief hearingassessment.

In one implementation, upon generating a hearing profile for a user, thesystem can, based on features of the hearing profile of the user,calculate a minimum number of frequency channels and/or a minimum FOGsufficient for a hearing-assistance device to execute the hearingprofile of the user. For example, the system can generate a hearingprofile for a user that includes ten unique gain values across thehuman-audible spectrum and, therefore, indicates that the minimum numberof frequency channels sufficient for a hearing-assistance device toexecute the hearing profile is equal to ten frequency channels.Likewise, the system can generate a hearing profile for a user thatincludes a maximum gain value of 50 decibels and, therefore, indicatesthat the minimum FOG sufficient for a hearing-assistance device toexecute the hearing profile is equal to 50 dB.

However, the system can generate a hearing profile in any other way suchas based on other types of hearing assessments including traditionalaudiogram tests (e.g., pure tone audiometry tests), speechdiscrimination tests, acoustic reflex tests, or via selection of apreset hearing profile.

5. HEARING-ASSISTANCE DEVICE OPTIONS

Generally, the system can access a set of hearing-assistance deviceoptions in Block S120. More specifically, the system can access acatalogue of hearing-assistance device options, wherein eachhearing-assistance device option in the catalogue details the specificcharacteristics of the associated hearing-assistance device. The systemcan access hearing-assistance device options that include specificationsfor a particular model of hearing-assistance device as well as a numberof variants of each hearing-assistance device model such as differentsizes of the same model or available tip sizes for the same model. Thesystem can access hearing-assistance device options that includespecifications of the form factor of the hearing-assistance deviceand/or a constraining dimension of the hearing-assistance device forsizing, a size of the hearing-assistance device (corresponding to rangesof the constraining dimension), FOG of the hearing-assistance device,number of frequency bands (or channels) of the hearing-assistancedevice, the bandwidth and spectral positioning of the frequency bands ofthe hearing-assistance device, the color of the hearing-assistancedevice, and/or the battery life (or battery capacity) of thehearing-assistance device. However, each hearing-assistance deviceoption can include any other specification of the representedhearing-assistance device.

The system can additionally access a hearing-assistance device cataloguethat can include hearing-assistance device options representinginvisible-in-canal hearing aids (hereinafter “IIC hearing aids”),completely-in-canal hearing aids (hereinafter “CIC hearing aids”), RIChearings aids, ITE hearing aids, receiver-in-the-ear hearing aids(hereinafter “RITE hearing aids”), behind-the-ear hearing aids(hereinafter “BTE hearing aids), or any other form factor of ahearing-assistance device.

Each hearing-assistance device option in the catalogue ofhearing-assistance device options defines a corresponding constrainingdimension relative to human ear anatomy, which is predictive of the sizeof the hearing-assistance device that is appropriate for a user's earcharacterized by a constraining dimension of a particular value. In oneimplementation, the system can access hearing-assistance device optionsfor RIC hearing aids that define a constraining dimension equal to adistance between the end of a user's forward helix to the top of theuser's ear canal (as shown in FIG. 2A). As a result, an appropriate sizeof an RIC hearing aid corresponds to the distance between the end of theuser's forward helix and the top of the user's ear canal. Additionallyor alternatively, a hearing aid option representing an ITE or RITEhearing aid can define a constraining dimension equal to the minimumdistance between the edge of a user's concha and the user's externalauditory meatus. In one implementation, the system can accesshearing-assistance device options that define the length and/or shape ofa two-dimensional edge defined relative to a user's ear anatomy. Forexample, a hearing-assistance device option can define an edge along auser's antihelix as a constraining dimension.

In one implementation, a hearing-assistance device option can definemultiple constraining dimensions if more specific size options areavailable (e.g., if different sized silicone tips or specifically shapedchassis are available for the hearing-assistance device).

In another implementation, a hearing-assistance device option can definemultiple types of tips, such as open tips or closed tips, each typecorresponding to a hearing sensitivity of the user (e.g., as measured bythe hearing assessment). For example, the system can select a closed tip(that reduces background noise) for users with high hearing sensitivity.Alternatively, the system can select an open tip for users with lowerhearing sensitivity.

6. CAPABILITY FILTERING OF HEARING-ASSISTANCE DEVICE OPTIONS

Generally, the system can filter the set of hearing-assistance deviceoptions based on the capabilities of each hearing-assistance devicerepresented by each hearing-assistance device option expressed in termsof the FOG of each hearing-assistance device and the number of frequencychannels of each hearing-assistance device in order to eliminatehearing-assistance devices from the set of hearing-assistance deviceoptions that are not capable of executing the hearing profile of theuser. More specifically, the system can: filter the set ofhearing-assistance device options to remove hearing-assistance deviceoptions in the set of hearing-assistance device options defining afull-on gain less than the minimum full-on gain indicated by the hearingprofile of the user and to remove hearing-assistance device options inthe set of hearing-assistance device options defining a number offrequency channels less than the minimum number of frequency channelsindicated by the hearing profile of the user. Thus, prior to rankingeach of the hearing-assistance device options based on subjective userpreference, the system eliminates options that are not capable ofcompensating for a user's hearing deficiency.

In one implementation, the system can also remove hearing-assistancedevice options from the set of hearing-assistance device options basedon the boundary locations of frequency bands corresponding to eachfrequency channel of the hearing-assistance device represented by eachhearing-assistance device option. For example, the system can: access ahearing profile of a user indicating a large variation between adjacentfrequency bands; and remove hearing-assistance device options thatinclude only a single frequency channel spanning the adjacent frequencybands of the hearing profile.

7. EAR SIZING IMAGE ACQUISITION

Generally, the system can access an image of an ear of the user in BlockS130. More specifically, the system can prompt the user, via a mobileapplication, to record an image of one or both of the user's ears. Thesystem can also provide further instructions to the user such as toinclude a size reference in the image and/or to record the image at aparticular angle and/or distance relative to the user's ear.

In one implementation, the system can prompt the user to include a sizereference when recording an image of the user's ear, wherein the sizereference can include any standardized currency that can be associatedwith a consistence size.

In another implementation, the system can execute a computer visionmodel (further described below) that can evaluate the efficacy of theimage recorded by the user in real time to determine whether locationsof particular visual features of the ear can be detected from therecorded image, wherein the particular visual features are associatedwith the constraining dimensions corresponding to form factors ofhearing-assistance devices in the catalogue of hearing-assistancedevices.

In yet another implementation, the system can prompt the user to recorda video (i.e., a set of images) of her ear while translating or rotatingthe camera such that the system can generate a three-dimensional modelof the user's ear, as is further described below. In thisimplementation, the system can indicate an arc or other path throughwhich the user may move a smartphone or other video recording device.

However, the system can obtain an image of a user's ear in any otherway.

8. DETECTING CONSTRAINING DIMENSIONS

As shown in FIG. 2, in Block S132, the system can detect a constrainingdimension for a form factor based on the image of the ear of the user.More specifically, the system can identify locations of physicalfeatures of the user's ear and measure the distance, angle, and or shapeof the physical features based on the locations of the physical featuresin the recorded image of the user's ear in order to calculate aparticular constraining dimension for the user's ear. The system cancalculate multiple constraining dimensions in order to calculate sizesfor a set of hearing-assistance devices characterized by multipledifferent form factors.

In order to detect accurate dimensions between the physical features ofthe user's ear, the system can scale the image based on a size referencein the image. More specifically, the system can: identify a sizereference in the image; extract a set of pixel-domain dimensions fromthe image; and scale the set of pixel-domain dimensions according to thesize reference to calculate the set of constraining dimensions. Thus,the system can extract more precise measurements on constrainingdimensions from a single image of the user's ear.

In one implementation, the system can prompt the user to position thesize reference at the same depth as the user's ear anatomy whenrecording the image and assume the depth of the size reference in theimage relative to the camera is the same as the depth of the user's earanatomy in the image relative to the camera. The system can then resizethe entire image based on the apparent size of the size reference in theimage.

Alternatively, the system can estimate a depth of the size referencerelative to the ear anatomy of the user utilizing computer visiontechniques. In this alternative implementation, the system can crop theimage such that the cropped version of the image only contains the earanatomy of the user and scale the cropped image based on the relativedepth between the ear anatomy in the image and the size reference andthe apparent size of the size reference in the image.

Additionally, the system can utilize concurrent sensor data such as fromaccelerometers and gyroscopes integrated with a user's mobile device(e.g., a smartphone or tablet computer) with the image recorded at theuser's mobile device to automatically scale the image. Furthermore, thesystem can fuse multiple images (e.g., from a video recorded by a user'smobile device) with concurrent sensor data in order to estimate thescale of the user's ear anatomy and/or construct a three-dimensionalmodel (e.g., a three-dimensional point cloud) representing the geometryof a user's ear anatomy in addition to the two-dimensional images of theuser's ear anatomy. Thus, the system can: access a set of images of theear of the user; generate a three-dimensional model of the ear of theuser based on the set of images; and extract the set of constrainingdimensions based on the three-dimensional model.

In one implementation, the system detects the location of the end of theuser's forward helix and the highest point of the user's ear canal inorder to measure the distance between these physical features, which canbe a constraining dimension of RIC hearing aids. Thus, the system candetect a minimum distance between a forward helix of the ear of the userand an ear canal of the ear of the user in order to filter RIC hearingaids from the set of hearing-assistance device options.

In another implementation, the system detects physical featuresincluding the perimeter of a user's concha cavum. The system can thencalculate the minimum diameter of the user's concha cavum as aconstraining dimension for CIC hearing aids. In one implementation, thesystem can utilize an edge detection algorithm together with thecomputer vision model (further described below) to identify theperimeter of the user's concha cavum in the image. Subsequently, thesystem can identify a centroid of the user's concha cavum based on theidentified perimeter and measure a diameter of the concha cavumcorresponding to a size of a CIC hearing aid.

In one implementation, the system can identify various anatomicalfeatures along the edges of the concha cavum, such as the user's tragus,the user's antitragus, the user's antihelix, or the crus of the user'santihelix. The system can then calculate a diameter or chord of theuser's concha cavum as a constraining dimension for a hearing-assistancedevice. Thus, the system can calculate a minimum diameter of a conchacavum of the ear of the user as a constraining dimension for ITE or CIChearing aids.

In yet another implementation, the system can identify and record theshape of the perimeter of the user's concha cavum. The system can thenutilize the shape of the user's concha cavum as a constraining dimensionto identify hearing-assistance devices that fit the user's ear anatomy.Therefore, the system can compare the shape of a user's concha cavum toa cross section of a hearing-assistance device to evaluate the fit ofthe hearing-assistance device.

Additionally, the system can also identify other physical features andmeasure other constraining dimensions of a user's ear anatomy such asthose pertaining to the concha cymba or the intertragal notch of theuser, depending on the form factors of hearing-assistance devices in thecatalogue of hearing-assistance devices.

However, the system can identify any physical feature of typical humanear anatomy and measure any constraining dimension that corresponds to asize of a hearing-assistance device characterized by a particular formfactor.

8.1 Computer Vision Model

In one implementation, the system can execute a computer vision model inorder to identify physical features of a user's ear anatomy. Morespecifically, the system can implement a convolutional neural networkto: identify ear anatomy in the image of the user's ear anatomy;identify select physical features based on the form factors ofhearing-assistance devices present in the catalogue ofhearing-assistance devices; and measure constraining dimensions of theuser's ear. The computer vision model can take in scaled and/orpreprocessed images of a user's ear anatomy and identify the location ofphysical features of the user by identifying bounding boxes within theimage, a particular pixel location, or a parameterized curve within theimage.

In one implementation, the system can process images of ear anatomy thathave been preprocessed by an edge detection algorithm yielding an edgedetected greyscale image for further analysis by the computer visionmodel.

In another implementation, the system can process multiple images of auser's ear anatomy in order to increase the confidence with which thecomputer vision model can identify physical features and/or constrainingdimensions of a user's ear anatomy. In one example, the system canprompt the user to record additional images of the user's ear anatomyuntil the system has achieved a threshold confidence level inidentifying physical features of the user's ear anatomy.

The system can also train the computer vision model based on a databaseof labeled ear images, wherein the labeling can be performed by humanstrained at identifying ear anatomy. For example, the system can enable auser interface for administrators to label a corpus of images of earanatomy with bounding boxes, singular points, or curves includingphysical features of interest in the images of ear anatomy. The systemcan then provide the labeled images as a set of training examples forthe computer vision model. The system can then execute standard trainingalgorithms such that the computer vision model can accurately identifythe physical features of interest within input images of user's earanatomy.

9. EAR ANATOMY FILTERING OF HEARING-ASSISTANCE DEVICE OPTIONS

Generally, in Block S140, the system can filter the set ofhearing-assistance device options associated with the form factor basedon the constraining dimension. More specifically, the system can removehearing-assistance device options that are characterized by sizes and/orform factors that do not correspond to values of constraining dimensionsas measured by the system.

In one implementation, the system can include a predetermined sizingcorrespondence table that relates particular ranges of values forconstraining dimensions to particular sizes and/or form factors ofhearing-assistance devices. For example, the system can access a tableindicating that if a distance between the end of a user's frontal helixand the closest point of the user's ear canal to the user's frontalhelix is between 15 and 20 millimeters then the user should fit a sizesmall RIC hearing aid of a particular model. In this example, the systemcan then remove from the set of hearing-assistance device options allRIC hearing aids of the particular model that are not a size small,thereby narrowing the number of devices that are eligible for selectionfor the user. For example, the system can, for each hearing-assistancedevice option in the set of hearing-assistance device options: identifya set of RIC hearing aid options in the set of hearing-assistance deviceoptions defining a form factor conforming to the minimum distancebetween the forward helix of the ear of the user and the ear canal ofthe ear of the user (according to the sizing correspondence table);identify a set of ITE hearing aid options in the set ofhearing-assistance device options defining a form factor conforming tothe minimum diameter of the concha cavum of the ear of the user(according to the sizing correspondence table); and generate the firstsubset of hearing-assistance device options comprising the set ofreceiver-in-canal hearing aid options and the set of in-the-ear hearingaid options. Thus, to determine which hearing-assistance device optionscorrespond to the measured constraining dimensions, the systemidentifies the subset of hearing-assistance device options in the set ofhearing-assistance device options that define sizes or form factorscorresponding to ranges of the constraining dimension spanning themeasured constraining dimension.

In another implementation, the system can execute a classification modelbased on the detected constraining dimensions. The classification modelcan be a neural network or other machine learning model that classifiesa set of input constraining dimensions that describe a user's earanatomy to calculate the best form factor or particular size of ahearing-assistance device for each form factor represented in thecatalogue of hearing-assistance devices.

In yet another implementation, wherein the system detects the perimeterof the user's concha cavum as a constraining dimension, the system canexecute a pattern matching algorithm to find a hearing-assistance devicewith a shape most complimentary to the detected shape of the user'sconcha cavum.

In implementations in which the system accesses a set ofhearing-assistance device options that define a form factor that furtherindicates a set of tip sizes for the hearing-assistance devicerepresented by the hearing-assistance device option, the system can alsofilter out tip sizes that do not correspond with the measuredconstraining dimensions of the user's ear.

However, the system can filter hearing-assistance device optionsrepresenting hearing-assistance devices that are not likely to fit a setof constraining dimensions measured based on an image of the user's ear.

10. USER PREFERENCES

Generally, in Block S150, the system accesses a set of preferences ofthe user. More specifically, the system can: prompt the user to completea survey indicating preferable characteristics for herhearing-assistance device; and/or access historical data of preferablecharacteristics for hearing-assistance device expressed by similarusers. The system can prompt the user to answer survey questions toindicate a preferred color, a preferred form factor, a preferred pricerange, a preferred battery life, a preferred material, or any otherpreferred characteristic of a hearing-assistance device in order tobetter provide hearing-assistance device with user-preferredcharacteristics.

In one implementation, the system can prompt the user to complete asurvey with information indicating the user's intended use case for thehearing-assistance device. For example, the user can indicate that sheintends to use the hearing-assistance device in especially noisyenvironments (such as a large restaurant), to attenuate a loud sound ina construction site setting, in home environment, or any otherenvironment. The system can then translate these preferences to specificselection criteria or ranking criteria. Alternatively, the system canincorporate the user's expressed preferences as a variable in a rankingmodel further described below.

In one implementation, the system can obtain additional user preferencedata from prior interactions with other users. For example, the systemcan track hearing-assistance device selections made by prior users ofthe system to identify correlations between basic demographic data(e.g., age, sex, occupation) for a user and expressed user preferencesfor particular characteristics of hearing-assistance devices. The systemcan therefore track final selections and rejections ofhearing-assistance devices delivered to prior users. The system can theninput these selections and rejections along with the demographic dataassociated with each corresponding prior user into the ranking modelfurther described below.

In one implementation, the system can filter the set ofhearing-assistance device options based on the price of eachcorresponding hearing-assistance device and the preferred price range ofthe user. Thus, each hearing-assistance device option can represent aspecific feature configuration of a hearing-assistance device and anassociated price of that configuration.

However, the system can obtain and incorporate user preferences forparticular hearing-assistance device characteristics in any other way.

11. HEARING-ASSISTANCE DEVICE RANKING

Generally, in Block S152, the system can rank the filtered subset ofhearing-assistance device options based on the set of preferences of theuser. More specifically, the system can execute a ranking model to ranka set of remaining hearing-assistance device options. The system canexecute the ranking model to generate a confidence score for eachhearing-assistance device option that the system did not filter out ofconsideration based on the constraining dimensions of the user or theuser's hearing profile. The ranking model takes in a vector of userpreferences and outputs the confidence score representing the likelihoodthat the user selects the hearing-assistance device given the vector ofuser preference. Thus, the system can utilize any classificationalgorithm to execute the ranking model. Upon calculating a confidencescore for each remaining hearing-assistance device option, the systemcan order the remaining hearing-assistance device options according tothe confidence score, thereby ranking the hearing-assistance deviceoptions.

The system can train the ranking model based on selection and rejectiondata from prior users of the system. In one implementation, the systemtrains the ranking model based on a set of training examples, whereineach training example includes a preference vector of a prior user andat least one selection of a hearing-assistance device made by the sameprior user. Additionally, the system can include negative trainingexamples of hearing-assistance devices delivered to the user butreturned by the user.

In one example, the system can access a set of user preferences thatinclude an anticipated usage rate of the user (e.g., five hours perday). The system can then correlate this user preference with aparticular attribute of a hearing-assistance device, such as the batterycapacity of a hearing-assistance device. Thus, the system can rank thefiltered subset of hearing-assistance device options based on the set ofpreference of the user and based on the battery capacity of thehearing-assistance device represented by each hearing-assistance deviceoption in the filtered subset of hearing-assistance device options.

However, the system can rank the set of filtered (i.e. remaining)hearing-assistance device options according to any other model or metricassociated with the likelihood of the user selecting a particularhearing-assistance device given the set of preferences expressed by theuser. Alternatively, the system can rank the hearing-assistance deviceoptions, in part or entirely based on administrative preferences forparticular hearing-assistance devices options in the set of filterhearing-assistance device options. For example, the system can weightthe ranking of each hearing-assistance device option according to thepreferences of an administrator, thereby increasing the rank ofpreferred hearing-assistance device options.

12. SELECTION AND DELIVERY

Generally, in Block S160, the system selects a subset of highest-rankedhearing-assistance device options from the filtered subset, the subsetof highest-ranked hearing-assistance device options representing a setof hearing-assistance devices to be delivered to the user. Morespecifically, the system selects a number of hearing-assistance devicesbased on the ranking of filtered hearing-assistance device options andthe previously obtained set of user preferences. In one implementation,the system selects hearing-assistance device options for delivery to theuser according to selection criteria specified based on expressedpreferences of the user and/or by an administrator of the system.

In one implementation, the system selects a subset of the filteredhearing-assistance device options corresponding to a predeterminednumber of the highest-ranked hearing device options. For example, thesystem can select the three highest-ranked hearing-assistance deviceoptions for delivery to the user.

In another implementation, the system establishes a set of selectioncriteria based on administrative or user preferences. For example, thesystem can execute a selection criterion established by an administratorthat at least one of the selected hearing-assistance device options bean RIC hearing aid. In an alternative example, the system can prompt theuser to respond to a survey question inquiring as to whether the userhas a preferred form factor for her hearing-assistance device. If theuser responds that she prefers CIC hearing aids, then the system canexecute a selection criterion specifying that only CIC hearing aids beselected in Block S170. Assuming the system is executing a selectioncriterion, the system can select the highest-ranked hearing-assistancedevice option that satisfies the selection criterion.

In one example, the system can, in accordance with a selectioncriterion, select a set of highest-ranked hearing-assistance devicescomprising: at least one RIC hearing aid, wherein the RIC hearing aid isthe highest-ranked RIC hearing aid in the set of hearing-assistancedevice options; and at least one ITE hearing aid, wherein the ITEhearing aid is the highest-ranked ITE hearing aid in the set ofhearing-assistance device options. Thus, when executing this selectioncriterion, the system ensures that at least one RIC hearing aid and atleast one ITE hearing aid is delivered to the user, thereby guaranteeingthe user an opportunity to experiment with both types of hearing aids.

Generally, the system can apply administrative selection criteria inorder to increase variety in the selected subset of hearing-assistancedevices delivered to the user thereby improving the likelihood that atleast one of the hearing-assistance devices may be chosen by the user.

In one implementation, the system can resolve conflicts betweenselection criteria established by the administrator and selectioncriteria established by the user. For example, an administrator of thesystem may establish a selection criterion that the system select a setof hearing-assistance devices characterized by a variety of form factorsfor delivery to the user, while the user may specify selection criterionto select hearing-assistance devices of only a single form factor. Incases of conflict between selection criteria, the system can prioritizeeither a user's selection criteria or the administrator's selectioncriteria. Furthermore, the system can prioritize each selectioncriterion on a criterion-by-criterion basis. For example, anadministrator of the system can specify that particular selectioncriterion not be compromised upon conflicts with user specifiedselection criterion.

Once the system selects a subset of the filtered and rankedhearing-assistance device options, the system can prompt delivery of(i.e. dispatch) the hearing-assistance devices corresponding to theselected hearing-assistance device options to the user.

In one implementation, the system can select a subset ofhearing-assistance device options from a filtered set ofhearing-assistance device options without first ranking these optionsaccording to user preference and based solely on a set of selectioncriteria. Additionally or alternatively, the system can selecthearing-assistance device options based on any business-related orpromotional concern.

13. HEARING PROFILE CONFIGURATION

Generally, in Block S180, the system configures each hearing-assistancedevice in the set of delivered hearing-assistance devices with thehearing profile of the user. More specifically, upon receipt of ahearing-assistance device (e.g., delivered hours, days, or weeks later),the user may pair the hearing-assistance device to her computing device,such as over a local ad hoc wireless network. The system—executing onthe user's computing device—can then: link the hearing-assistance device(e.g., a unique identifier of the hearing-assistance device) to theuser's profile; retrieve the refined hearing profile generated duringthe initial assessment described above; and upload the refined hearingprofile to the hearing-assistance device.

The hearing-assistance device can then immediately begin: detectingaudio signals in; processing these audio signals according to therefined hearing profile; and outputting these processed audiosignals—now with select frequency bands amplified according to therefined hearing profile—via a speaker integrated into thehearing-assistance device. The hearing-assistance device can thereforeimplement the refined hearing profile generated during the hearingassessment, which was performed on the user's computing device withanother audio output device (e.g., a separate set of headphones).

However, because the hearing-assistance device may (or is likely) toexhibit a frequency response that differs from the frequency response ofthe user's computing device and headphones, the refined hearing profilegenerated during the hearing assessment may fully compensate for theuser's hearing loss when implemented by the hearing-assistance device.Nonetheless, the refined hearing profile generated during the hearingassessment may better represent the user's hearing augmentation needsthan a nominal hearing profile when implemented by thehearing-assistance device. Therefore, the hearing-assistance device caninitially implement the refined hearing profile; and the system cancooperate with the hearing-assistance device to execute an on-devicehearing assessment and to modify the refined hearing profileaccordingly.

13.1 On-Device Hearing Assessment

In one variation, described in U.S. Pat. No. 10,595,135, which isincorporated by reference in its entirety, after uploading the user'shearing profile—generated during the initial assessment as describedabove—to the hearing-assistance device and once the user initiates anon-device hearing assessment, the system can execute a process forrevising the user's hearing profile similar to the hearing assessmentprocess described above. However, instead of selectively amplifying eachsoundbite based on test hearing profiles, the system can: upload thetest hearing profiles to the hearing-assistance device; confirm that thehearing-assistance device has activated the hearing profile (e.g., thedigital signal processor of the hearing device is executing a set ofdigital filters in order to amplify input sound according to theuploaded hearing profile); and play the raw soundbite (e.g., withoutamplification) such that the only amplification applied to the soundbiteis performed at the hearing-assistance device. Thus, the system canassess user preferences for the refined hearing profile given theparticular frequency response characteristics of the hearing-assistancedevice.

The systems and methods described herein can be embodied and/orimplemented at least in part as a machine configured to receive acomputer-readable medium storing computer-readable instructions. Theinstructions can be executed by computer-executable componentsintegrated with the application, applet, host, server, network, website,communication service, communication interface,hardware/firmware/software elements of a user computer or mobile device,wristband, smartphone, or any suitable combination thereof. Othersystems and methods of the embodiment can be embodied and/or implementedat least in part as a machine configured to receive a computer-readablemedium storing computer-readable instructions. The instructions can beexecuted by computer-executable components integrated bycomputer-executable components integrated with apparatuses and networksof the type described above. The computer-readable medium can be storedon any suitable computer readable media such as RAMs, ROMs, flashmemory, EEPROMs, optical devices (CD or DVD), hard drives, floppydrives, or any suitable device. The computer-executable component can bea processor but any suitable dedicated hardware device can(alternatively or additionally) execute the instructions.

As a person skilled in the art will recognize from the previous detaileddescription and from the figures and claims, modifications and changescan be made to the embodiments of the invention without departing fromthe scope of this invention as defined in the following claims.

I claim:
 1. A method comprising: accessing a set of hearing-assistancedevice options, each hearing-assistance device option defining a formfactor of a hearing-assistance device, in a set of hearing-assistancedevices; accessing an image of an ear of the user; detecting the ear ina region of the image; extracting a set of features from the region ofthe image; interpreting a set of constraining dimensions of the ear ofthe user based on the set of features; identifying a subset ofhearing-assistance device options, in the set of hearing-assistancedevice options, defining form factors conforming to the set ofconstraining dimensions; and selecting a first hearing-assistance deviceoption from the subset of hearing-assistance devices.
 2. The method ofclaim 1, wherein selecting a first hearing-assistance device option fromthe subset of hearing-assistance devices comprises: accessing a set ofpreferences of the user; ranking the subset of hearing-assistance deviceoptions based on the set of preferences of the user; selecting a firsthearing-assistance device option, from the subset of hearing-assistancedevice options, corresponding to a highest rank in the subset ofhearing-assistance device options.
 3. The method of claim 1: whereinaccessing the set of hearing-assistance device options comprisesaccessing the set of hearing-assistance device options, eachhearing-assistance device option defining a form factor and defining aset of tip sizes available for the hearing-assistance device; whereindetecting the set of constraining dimensions in the image of the ear ofthe user comprises detecting a shape of a concha cavum of the ear of theuser; and further comprising, for each hearing-assistance device optionin the subset of hearing-assistance device options, identifying a tipsize of the hearing assistance device in the set of tip sizes availablefor the hearing-assistance device conforming to the shape of the conchacavum of the ear of the user.
 4. The method of claim 1: whereinaccessing the image comprises accessing a set of images of the ear ofthe user; wherein extracting the set of features from the region of theimage comprises generating a three-dimensional model of the ear of theuser based on the set of images; and wherein interpreting the set ofconstraining dimensions of the ear of the user extracting the set ofconstraining dimensions from the three-dimensional model.
 5. The methodof claim 1: wherein interpreting the set of constraining dimensionsbased on the image of the ear of the user comprises: identifying a sizereference in the image; extracting a set of pixel-domain dimensions fromthe image; scaling the set of pixel-domain dimensions according to thesize reference to calculate the set of constraining dimensions; andfurther comprising extracting the set of constraining dimensions fromthe image of the ear of the user, the constraining dimensionscomprising: a minimum distance between a forward helix of the ear of theuser and an ear canal of the ear of the user; and a minimum diameter ofa concha cavum of the ear of the user.
 6. The method of claim 5, whereinidentifying the subset of hearing-assistance device options comprises:identifying a set of receiver-in-canal hearing aid options in the set ofhearing-assistance device options, each receiver-in-canal hearing aidoption in the set of receiver-in-canal hearing aid options defining aform factor conforming to the minimum distance between the forward helixof the ear of the user and the ear canal of the ear of the user;identifying a set of in-the-ear hearing aid options in the set ofhearing-assistance device options, each in-the-ear hearing aid option inthe set of in-the-ear hearing aid options defining a form factorconforming to the minimum diameter of the concha cavum of the ear of theuser; and generating the subset of hearing-assistance device optionscomprising the set of receiver-in-canal hearing aid options and the setof in-the-ear hearing aid options.
 7. The method of claim 1, furthercomprising: generating a hearing profile for the user based on a hearingassessment of the user; and configuring the first hearing-assistancedevice represented by the first hearing-assistance device option withthe hearing profile for the user.
 8. The method of claim 7: whereinselecting the first hearing-assistance device option from the subset ofhearing-assistance device options comprises selecting a set ofhighest-ranked hearing-assistance device options from the subset ofhearing-assistance device options for delivery to the user, the set ofhighest-ranked hearing-assistance device options representing a set ofhighest-ranked hearing-assistance devices comprising: a highest-rankedreceiver-in-canal hearing aid; and a highest-ranked in-the-ear hearingaid; and wherein configuring the first hearing-assistance devicerepresented by the first hearing-assistance device option with thehearing profile for the user comprises configuring the set ofhighest-ranked hearing-assistance devices with the hearing profile forthe user.
 9. The method of claim 7: wherein generating the hearingprofile comprises generating the hearing profile for the user based onthe hearing assessment, the hearing profile specifying a minimumfull-on-gain and a minimum number of frequency channels of ahearing-assistance device capable of executing the hearing profile;wherein accessing the set of hearing-assistance device options comprisesaccessing the set of hearing-assistance device options, eachhearing-assistance device option: defining a full-on gain of thehearing-assistance device; defining a number of frequency channels ofthe hearing-assistance device; and defining the form factor of thehearing-assistance device; and wherein identifying the subset ofhearing-assistance device options comprises identifying the subset ofhearing-assistance device options, in the set of hearing-assistancedevice options: defining form factors conforming to the set ofconstraining dimensions; defining full-on gains greater than the minimumfull-on gain; and defining numbers of frequency channels greater thanthe minimum number of frequency channels.
 10. The method of claim 7,wherein generating the hearing profile for the user comprises:generating a baseline hearing profile for the user based on demographicdata of the user; receiving a set of hearing preferences of the userexpressed in response to listening to a series of soundbites comprisingrecognizable sounds amplified by variations of the baseline hearingprofile; and modifying the baseline hearing profile based on the set ofhearing preferences to generate the hearing profile for the user. 11.The method of claim 10, wherein receiving the set of hearing preferencesof the user comprises: rendering a first slider bar in a user interfacerepresenting a first parameter of a first soundbite of the series ofsoundbites, the first parameter representing full-on gain; adjusting thefirst parameter based on a first change in a position of the firstslider bar.
 12. The method of claim 11, further comprising: in responseto receiving confirmation of the user's input, rendering a second sliderbar in the user interface representing a second parameter of the firstsoundbite of the series of soundbites, the second parametercorresponding to a number of frequency channels; adjusting the secondparameter based on a first change in a position of the second sliderbar.
 13. The method of claim 12, wherein rendering the second slider barcomprises rendering the second slider bar in response to receivingconfirmation of the user's input exceeding a threshold value, renderinga second slider bar representing a second parameter.
 14. The method ofclaim 12, wherein rendering the second slider bar comprises renderingthe second slider bar in response to receiving confirmation of theuser's input falling below a threshold value, rendering a second sliderbar representing a third parameter.
 15. The method of claim 12: furthercomprising ranking the first parameter and second parameter by apredicted magnitude of perceived change during the hearing assessment;and wherein rendering a first slider bar in the user interface comprisesrendering a first slider bar representing a first ranked parameter. 16.The method of claim 12, further comprising ranking the first parameterand second parameter by sensitivity based on a sensitivity analysis ofthe user; and wherein rendering a first slider bar in the user interfacecomprises rendering a first slider bar representing a first rankedparameter.
 17. The method of claim 1, further comprising: generating ahearing profile for the user based on a hearing assessment of the userexecuted at a mobile device; configuring the first hearing-assistancedevice represented by the first hearing-assistance device option withthe hearing profile for the user; at a mobile device, in response towireless communication between the mobile device and the firsthearing-assistance device: rendering a slider, associated with aparameter of the hearing profile, within a user interface; outputting atone; and in response to a change in position of the slider within theuser interface: generating an updated hearing profile based on thehearing profile and the change in position of the slider; and uploadingthe updated hearing profile to the first hearing-assistance device. 18.A method comprising: accessing a set of hearing-assistance deviceoptions, accessing a set of preferences of the user; identifying asubset of hearing-assistance device options in the set ofhearing-assistance device options most likely to be selected by the userbased on the set of preferences of the user; and dispatching theselected set of hearing-assistance devices to the user.
 19. The methodof claim 18: further comprising generating a hearing profile for theuser based on a hearing assessment specifying a minimum full-on-gain anda minimum number of frequency channels of a hearing-assistance devicecapable of executing the hearing profile; wherein accessing the set ofhearing-assistance device options comprises accessing the set ofhearing-assistance device options, each hearing-assistance deviceoption: defining a full-on gain of the hearing-assistance device;defining a number of frequency channels of the hearing-assistancedevice; and defining the form factor of the hearing-assistance device;and configuring the selected set of hearing-assistance devicesrepresented in the subset of hearing-assistance devices with the hearingprofile for the user; and wherein identifying the first subset ofhearing-assistance device options comprises identifying the first subsetof hearing-assistance device options, in the set of hearing-assistancedevice options: defining form factors conforming to the set ofconstraining dimensions; defining full-on gains greater than the minimumfull-on gain; and defining numbers of frequency channels greater thanthe minimum number of frequency channels.
 20. The method of claim 18:further comprising: detecting a constraining dimension based on an imageof the ear of the user; identifying a first subset of hearing-assistancedevice options in the set hearing-assistance device options definingform factors conforming to the constraining dimension; wherein accessingthe set of hearing-assistance device options comprises accessing a setof hearing-assistance device options, each hearing-assistance deviceoption defining a form factor of the hearing-assistance device; whereinaccessing the set of hearing-assistance device options comprisesaccessing the set of hearing-assistance device options, eachhearing-assistance device option defining the form factor of thehearing-assistance device, the form factor conforming to a range of theconstraining dimension; and wherein identifying the first subset ofhearing-assistance device options in the set of hearing-assistancedevice options defining form factors conforming to the constrainingdimension comprises identifying the first subset of hearing-assistancedevice options in the set of hearing-assistance device options definingform factors conforming to ranges of the constraining dimension spanningthe constraining dimension.